Csaba Jakab

40 papers receiving 424 citations

Peers

Csaba Jakab
Comparison fields: 5 of 101
  • Animal Science and Zoology 69
  • Biotechnology 49
  • Neurology 42
  • Parasitology 27
  • Infectious Diseases 74
Replace Alejandro Suárez‐Bonnet with:
Alejandro Suárez‐Bonnet United Kingdom
Susumu TATEYAMA Japan
Mitja Gombač Slovenia
Dávid Švec Czechia
I. Dolka Poland
Oscar Illanes Saint Kitts and Nevis
Carmen M. H. Colitz United States
Daniel A. Ward United States
Giuseppe Passantino Italy
Robert D. Murnane United States
Csaba Jakab relative to Alejandro Suárez‐Bonnet United Kingdom Alejandro Suárez‐Bonnet's profile →
Citations per field
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Alejandro Suárez‐Bonnet · 1×
Citations per year

Countries citing papers authored by Csaba Jakab

Since Specialization
Citations

This map shows the geographic impact of Csaba Jakab's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Csaba Jakab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Csaba Jakab more than expected).

Fields of papers citing papers by Csaba Jakab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Csaba Jakab. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Csaba Jakab. The network helps show where Csaba Jakab may publish in the future.

Co-authors

The 25 scholars most cited alongside Csaba Jakab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Csaba Jakab Line = papers co-authored together Csaba Jakab links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200994
2 201151
3 201134
4 201321
5 200820
6 200818
7 201417
8 201115
9 201014
10 201112
11 201411
12 201410
13 201210
14 20108
15 20108
16 20128
17 20207
18 20097
19 20106
20 20135

About Csaba Jakab

Csaba Jakab is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Neurology, Surgery and Genetics, having authored 42 papers that have together received 433 indexed citations. Recurring topics across this work include Barrier Structure and Function Studies (10 papers), Veterinary Oncology Research (9 papers), Virus-based gene therapy research (5 papers), Animal Virus Infections Studies (4 papers), Hedgehog Signaling Pathway Studies (4 papers), Wnt/β-catenin signaling in development and cancer (3 papers), Neurological Disease Mechanisms and Treatments (3 papers) and Aquaculture disease management and microbiota (3 papers). The work is most often cited by research in Animal Science and Zoology (69 citations), Biotechnology (49 citations), Neurology (42 citations), Parasitology (27 citations) and Infectious Diseases (74 citations). Csaba Jakab has collaborated with scholars based in Hungary, United Kingdom and United States. Frequent co-authors include Miklós Rusvai, P. Gálfi, Gábor Andócs, Helmut Renner, Lajos Balogh, Á. Szász, Janina Kulka, Gyula Balka, Zoltán Demeter and Míra Mándoki. Their work appears in journals such as Acta Veterinaria Hungarica, Frontiers in Veterinary Science, Avian Pathology, Journal of Fish Diseases and Journal of Veterinary Diagnostic Investigation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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